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Real-Time Monitoring of Structural Health with Wireless sensor Networks in IoT Infrastructure 3

Real-Time Monitoring of Structural Health with Wireless Sens...

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3rd ieee international conference on Automation and Computation, AUTOCOM 2025

作者： Bhushan, Bharat Pushparajesh, V. Bethanney Janney, J. Sahoo, Girija Shankar Aggarwal, Prateek Das, Dibyasundar Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Biomedical Engineering Tamil Nadu Chennai India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Centre for Cyber Security Odisha Bhubaneswar India

ISBN: (纸本)9798331542375

Wireless sensor Networks for structural health monitoring of infrastructure are now becoming an IoT. It provides the ability to collect and analyze survivability data in real-time to enable continuous structural health monitoring for buildings, bridges, and other critical infrastructure. The purpose of this abstract is to introduce Real-time Monitoring with Wireless sensor Networks in IoT Infrastructure. Wireless sensor Networks are used in structural health monitoring. They are typically composed of many distributed, cheap sensors embedded in the structure that communicate wirelessly to a central monitoring station. Those sensors, including temperature, strain and vibration, are critical in detecting potential structural problems. This data gets transmitted to a cloud for processing, which provides indications of an unusual characteristic or predictive failure. Compared to the traditional methods, there are several advantages of applying WSN for real-time structural health monitoring. Lead leads provide real-time updates on the condition of a bridge that allows for continuous monitoring, with advanced sensors pinpointed through its structure. It will assist in keeping the infrastructure safe and affordable by guaranteeing rapid time-to-resolution. In addition, WSNs have low implementation costs and do not interfere too much with the structure of large structures. © 2025 ieee.

关键词： Wireless sensor networks

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sensor Networks for Real-Time Air Quality Monitoring in Smart Cities 3

Sensor Networks for Real-Time Air Quality Monitoring in Smar...

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3rd ieee international conference on Automation and Computation, AUTOCOM 2025

作者： Das, Neeraj Katyal, Ashu Dutta, Pratik Aggarwal, Prateek Pavan, P.S. Vincent, Kalist Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India Odisha Bhubaneswar India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh Baddi174103 India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Electrical and Electronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331542375

This requires ubiquitous sensor networks to monitor and instantaneously predict dangerous gas concentrations at ground level deployed within smart city environments. A sensor network is a collection of many distributed sensors that can be used together to gather data in real-time and from standard logs across an environment, generally allowing users to see, hear, or feel whether emissions are entering their air as they happen. Cities attaching these sensor networks can provide real-time air quality data for municipalities and citizens taking control of our health. It can analyze pollution hotspots, detect trends and patterns over time, and act as an early warning system for dangers. Such work creates a framework for interventions to be undertaken quickly and efficiently to reduce air pollution as soon as possible and work towards protecting residents' public health. sensor networks can also provide historical data, which is necessary for tracking long-term trends and assessing how effective pollution control measures have been. Furthermore, this information can validate city-specific policies and exercise recommendations for reducing air pollution in smart cities. It will give decision-makers and citizens the data they must act on while making well-informed decisions for cleaner air in their cities. © 2025 ieee.

关键词： Air quality

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Application and Evaluation of Real-Time Analysis Algorithms in Dynamic Data Processing systems

Application and Evaluation of Real-Time Analysis Algorithms ...

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Integrated Circuits and Communication systems (ICICACS), ieee international conference on

作者： Si Chen College of Digital Business Liaoning Vocational University of Technology Jinzhou Liaoning China

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Dynamic data processing systems are key technologies in modern data-driven applications, widely used in fields such as the Internet of Things, finance and healthcare. This study explores the application and evaluation of real-time analytical algorithms for dynamic data processing. An efficient algorithmic framework combining adaptive windowing, incremental learning and distributed computing is proposed to achieve low-latency and high-accuracy decision-making capabilities. Through experimental validation in a real data streaming environment, the results show that the proposed algorithm significantly outperforms traditional algorithms with about 35% reduction in latency and 20% improvement in prediction accuracy. The research results in this paper show that the real-time analysis algorithm has a promising application in dealing with dynamic heterogeneous data streams. Meanwhile, the article also discusses the limitations and future optimisation directions of the method, which provides a reference for further research in related fields.

关键词： Performance evaluation Incremental learning Accuracy Heuristic algorithms Data processing Prediction algorithms Real-time systems Low latency communication distributed computing Streams

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IoT and sensor-based Water Quality Monitoring for Sustainable Management of Water Resources 3

IoT and Sensor-based Water Quality Monitoring for Sustainabl...

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3rd ieee international conference on Automation and Computation, AUTOCOM 2025

作者： Sidhu, Amritpal Bahri, Dimple Poornapushpakala, S. Agarwal, Trapty Ahluwalia, Gunveen Chatterjee, Pubali Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Centre for Cyber Security Odisha Bhubaneswar India

ISBN: (纸本)9798331542375

we are now moving into an era where the Iota and sensor-based technologies can monitor many parameters, including water quality. Since fresh, potable water is becoming increasingly scarce in many parts of the globe, maintaining a clean and sustainable source for consumption remains one of our biggest challenges today. This challenge can be addressed by leveraging IoT and sensor-based systems that accumulate data from several devices plus study it toward make insight designed meant for better executive. Most available IoT and sensor-based water quality monitoring systems use a network of devices, generally called sensors or data loggers that are connected to take in the multiple variables related to parameters like pH levels, dissolved oxygen placeholders d, and pollutants. This data is subsequently integrated with scientific algorithms and machine learning, which helps to determine water quality fluctuations in near real-time. These systems can be combined with geographic information systems, illuminating the data and making it mappable so that problem areas will likely emerge. IoT and sensor-based water quality monitoring are advantageous against conventional methods in terms of better accuracy, increased efficiency, cost-effectiveness to monitor long term, and the ability to demonstrate effective real-time information about water fettle. Information like this can be critical for managing water resources, as it can identify potential problems such as contamination or water running out. It optimizes these technologies to monitor remote locations, decreasing human labor requirements and enabling real-time decision-making in sustainable water resource management. © 2025 ieee.

关键词： Water management

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IOT and sensor-Based Flood Monitoring and Warning systems for Disaster Management 3

IOT and Sensor-Based Flood Monitoring and Warning Systems fo...

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3rd ieee international conference on Automation and Computation, AUTOCOM 2025

作者： Chitra, P. Acharjya, Kalyan Ojha, Varun Das, Priyadarshi Faiz, Ayaan Rao, Srikrishna Baskar Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Department of Civil Engineering Odisha Bhubaneswar India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India Karnataka Bangalore India

ISBN: (纸本)9798331542375

The Internet of Things, which has sensors for monitoring floods and generating alerts, reflects the most contemporary use-case of these solutions in disaster management. Using linked devices and sensors, these systems gather real-time information concerning water levels, weather aspects, and other environmental factors associated with flooding. This data can now produce precise flood forecasts and alerts, giving communities the information they need for large weather events with a better idea of when disasters may strike. Advantages of IOT and sensor-based flood monitoring systems: sensor cadmium selenium photocells, sharp water & infrared sensors, which include water level sensors, rain gauges, and temperature sensors in places exposed to floods. They do this by involving sensors installed throughout the city that monitor water levels or rainfall and can relay fluctuations to a central box. The data is then processed by sophisticated algorithms, resulting in flood forecasts and alerts that can be accessed via web-based platforms or mobile apps. One significant benefit of these systems is real-time flood data with accurate results that help communities evacuate and other disaster mitigation actions. These systems can also be linked to established emergency response systems that serve as an information source for graduate disaster management. These sensors and IOT-based flood monitoring systems also make for great innovative Disaster Management tools that will increase awareness, leading to better preparedness and response time between the occurrences of a natural disaster like floods with communities. © 2025 ieee.

关键词： Information management

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Smart Transportation systems: The Role of IoT and sensor-Based Solutions 3

Smart Transportation Systems: The Role of IoT and Sensor-Bas...

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3rd ieee international conference on Automation and Computation, AUTOCOM 2025

作者： Agarwal, Ankita Seth, Kanika Sahoo, Shreeya Swagatika Parmar, Yuvraj Dasarathy, A.K. Siva Sangari, A. Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Centre for Cyber Security Odisha Bhubaneswar India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India Department of Civil Engineering Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Information Technology Tamil Nadu Chennai India

ISBN: (纸本)9798331542375

Smart transportation systems are sophisticated technology solutions that deploy the Internet of Things (IoT) and sensor-based data platforms to transform one's existing erratic transportation network into an efficient system. The Internet of Things, which combines all devices and systems connected to the Internet, is changing our management and operation of transportation systems. Real-time data from sensors installed on vehicles, infrastructure, and other transport assets is one of the biggest benefits IoT can offer to transportation. This data will reduce traffic congestion, improve road safety, and help buses move smoothly in terms of traffic flow. A good way of illustrating this is through sensors equipped with traffic lights that communicate to the cars, where they can adjust between red and green light times while in action, thus causing fewer accidents on the road. loT likewise can lessen energy consumption and emissions, driving by way of the sustainability lens on transportation systems. Smart traffic management systems can adjust routes for vehicles, saving fuel and emissions. Cars and even electric vehicles can be configured using the same platform through this system will deliver higher efficiency for managing charging stations. Additionally, IoT and sensor integration are important for the growth of autonomous vehicles. These vehicles need immediate input from cameras, radars, and LiDARs to move around safely. IoT will allow these vehicles to communicate, and the transportation infrastructure will lead to a safer means of transport. © 2025 ieee.

关键词： Traffic congestion

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Security and Privacy Challenges in IoT and sensor Networks: A Review of Current Solutions 3

Security and Privacy Challenges in IoT and Sensor Networks: ...

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3rd ieee international conference on Automation and Computation, AUTOCOM 2025

作者： Sonti, V.J.K. Kishore Singh, Daljeet Pal Sood, Gourav Maheshwari, Bharat Vashisht, Nitish Manu, S.E. Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Centre for Cyber Security Odisha Bhubaneswar India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India Karnataka Bangalore India

ISBN: (纸本)9798331542375

Storage capacity is not a concern. sensor networks and IoT have transformed storage the way data is stored in multiple ventures. However, this increase in connected devices has also led to various security and privacy questions. This abstract aims to provide an insightful summary of some existing solutions to these pain points. They provided effective messages on device networks vulnerable to intrusion and were able to broadcast full security into IoT with sensor vulnerabilities. It may allow attackers to steal data, manipulate systems, or access them using fake credentials. Intrusion detection systems were created to solve the problems with many threats, such as secure protocols and authentication mechanisms. Another important aspect is privacy since these devices collect a large amount of data that can be used to infer potentially sensitive personal information. Some solutions to protect privacy in IoT and sensor networks have been suggested, such as encryption methods, data anonymization algorithms, or access control mechanisms. In addition, scalability, energy-efficient design, and cost are key challenges in devising such security and privacy solutions. To that end, research is being conducted to enhance existing solutions and develop new methods and technologies for tackling these challenges. To sum up, IoT and sensor networks are inherently rewarding technologies whose benefits far outweigh their drawbacks, but justifiably, many threats must be cleared to gain those attributes at the expense of reasonable security and privacy potentials. The current solutions are baseline, but they need continuous upgradation to ensure the safety and privacy of users in such a fast-moving technology world. © 2025 ieee.

关键词： Authentication

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Tool Condition Prediction in High-Speed Milling Using Deep Q-Networks (DQN) and sensor Fusion Data 3

Tool Condition Prediction in High-Speed Milling Using Deep Q...

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3rd ieee international conference on Automation and Computation, AUTOCOM 2025

作者： Dilli Ganesh, V. Duklan, Nitin Alabdeli, Haider Johri, Prashant Mohanraj, T. Venkatesh, R. Department of Mechanical Engineering Chennai India Uttaranchal University Dehradun India College of Technical engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq School of Computing Science and Engineering Galgotias University Greater Noida India Karpagam Academy of Higher Education Department of Computer Science Engineering Coimbatore India Department of Physics Dindigul India

ISBN: (纸本)9798331542375

Highly effective and reliable high-speed milling depends on the timely tool condition monitoring (TCM) check. In this paper, we propose a novel approach for tool condition prediction based on DQN with sensor fusion data. Both contact and non-contact sensors such as, vibrational, force, and acoustic emission sensors are utilized to gather data in real time during milling. The information collected by these sensors are integrated into a number of important features to be used in DQN model to learn the prediction of tool wear and possible failure. The DQN model is built to learn from the response of the milling environment characterized by tool condition in terms of wear and the remaining useful life (RUL). The results derived from experiments tend to show that the utilised DQNbased model has better quantitative values for accuracy, precision, recall, and F1-score than classical machine learning models like artificial neural networks (ANN), support vector regression (SVR), decision trees and etc. The integration of the sensor data enhances the overall prediction reliability, a factor which is highly achieved from the fusion of the data received from the vibration, force and acoustic emission sensors. The overall system proposed has significant application for real time implementation and demonstrates relatively short prediction time and is less sensitive to changes in the machining conditions. This proposed methodology is a feasible approach for improving tool life and reducing time needed for high speed milling applications. © 2025 ieee.

关键词： Milling (machining)

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Enabling Smart Farming with IoT and sensor Networks: Case Studies from Developing Countries 3

Enabling Smart Farming with IoT and Sensor Networks: Case St...

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3rd ieee international conference on Automation and Computation, AUTOCOM 2025

作者： Garg, Mohan Parui, Souvik Kumar Kandhari, Harsimrat David, Roshita Lakshmi, S. Naval, Preeti Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Centre for Cyber Security Odisha Bhubaneswar India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798331542375

Smart Farming with IOT and sensor Networks is an advanced technology that enables traditional farmers to reduce waste and introduce intelligence in measuring the productivity of crops. The papers show how deploying IOT and sensor networks has contributed to enhancing productivity, reducing costs, and sustainability through a few successful case studies spanning regions under development. IOT and sensor Networks for Agriculture: Low-cost sensors and communication devices with data analytics help collect and analyze real-time information from farms. Along with weather forecasts, soil analysis, and other useful insights, it helps farmers take technocratic actions, eventually allowing them to use their resources better. IOT and sensor networks are particularly useful in developing countries, where small-scale farmers often cannot access modern technologies and information. Farmers using IOT systems for drip irrigation can use their mobile phones to control watering remotely and thus increase water efficiency significantly, as was the case in India. Leveraging sensor networks to advance precision farming has successfully grown crops with higher yields and less fertilizer use in Africa. Using IOT and sensor networks in the application layer can significantly enhance food security, diminish ecological footprint, and foster sustainable agricultural practices, particularly in developing countries. The world has a later taste of the benefits that would eventuate in one dark-haired roommate becoming somewhat more bearded and less university student-like than ever before;there is still much research to come on this technology, which could change the face (not beard)of global agriculture - improving livelihoods for millions upon million small-scale farmers. © 2025 ieee.

关键词： Crops

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Proceedings of IPDRM 2019: 3rd Annual Workshop on Emerging Parallel and distributed Runtime systems and Middleware - Held in conjunction with SC 2019: The international conference for High Performance computing, Networking, Storage and Analysis

Proceedings of IPDRM 2019: 3rd Annual Workshop on Emerging P...

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3rd ieee/ACM Annual Workshop on Emerging Parallel and distributed Runtime systems and Middleware, IPDRM 2019

ISBN: (纸本)9781728159935

The proceedings contain 6 papers. The topics discussed include: assessing the performance impact of using an active global address space in HPX: a case for AGAS;sequential codelet model of program execution - a super-codelet model based on the hierarchical turing machine;ADVERT: an asynchronous runtime for fine-grained network systems;design and evaluation of shared memory communication benchmarks on emerging architectures using MVAPICH2;characterizing the performance of executing many-tasks on summit;and leveraging network-level parallelism with multiple process-endpoints for MPI broadcast.

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